The long term goal of this research is to better understand the functional organization and dynamics of the cerebral cortex. It is proposed to optically record neuronal activity from the surface of the visual cortex of macaque monkeys, and apply to the data an extension of the Karhunen-Loeve principal component (or empirical eigenfunction) analysis.The investigators' preliminary analysis of such data has shown that seemingly noisy optical signals contain a small number of spatially segregated dynamical components. This study will: 1) Establish whether these components correspond to known cortical structures or reveal new ones; 2) Search for visual stimuli that elicit only a single component in the response; 3) Investigate the contribution of known neuronal sub- populations (streams) to the optically-monitored neuronal activity by using visual stimuli that excite only certain cell populations, such as the magnocellular- projecting (M) cells, or only one class of photoreceptors; 4) Silence selected neuronal populations by injecting the local anesthetic Lidocaine into portions of the lateral geniculate nucleus (LGN); 5) Apply the same analysis techniques to data from neural models of the cortex, and show that the essence of the models can be captured by a much smaller set of dynamical equations (this should enable qualitative improvements in computational speed and data compression); and 6) show that the empirical eigenfunctions provide new objective measures of neuronal activity and connectivity applicable to relatively large cell populations.